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Anonymizer

The Anonymizer extension provides a function for anonymizing various data types. This function returns a fake value for anonymizing which matches the original data. For example, an email would be replaced with a fake email.

Data Types

Anonymizer supports the following data types:

Address

  • ADDRESS_BUILDINGNUMBER
  • ADDRESS_CITY
  • ADDRESS_COUNTRY
  • ADDRESS_COUNTRYCODE
  • ADDRESS_FULLADDRESS
  • ADDRESS_LATITUDE
  • ADDRESS_LONGITUDE
  • ADDRESS_STATE
  • ADDRESS_STATEABBR
  • ADDRESS_STREETADDRESS
  • ADDRESS_STREETADDRESSNUMBER
  • ADDRESS_STREETNAME
  • ADDRESS_TIMEZONE
  • ADDRESS_ZIPCODE
  • ADDRESS_ZIPCODEBYSTATE

Name

  • NAME_FULLNAME
  • NAME_FIRSTNAME
  • NAME_LASTNAME
  • NAME_TITLE
  • NAME_USERNAME

ID

  • ID_SSN

Credit Card

  • CREDITCARD_CREDITCARDTYPE
  • CREDITCARD_CREDITCARDNUMBER
  • CREDITCARD_CREDITCARDEXPIRY

Company

  • COMPANY_DEPARTMENT
  • COMPANY_PRODUCTNAME
  • COMPANY_PRICE
  • COMPANY_PROMOTIONCODE
  • COMPANY_NAME
  • COMPANY_INDUSTRY
  • COMPANY_URL
  • COMPANY_BIC
  • COMPANY_IBAN

Demographic

  • DEMOGRAPHIC_RACE
  • DEMOGRAPHIC_SEX
  • DEMOGRAPHIC_MARITALSTATUS
  • DEMOGRAPHIC_DEMONYM

Education

  • EDUCATOR_CAMPUS
  • EDUCATOR_COURSE
  • EDUCATOR_SECONDARYSCHOOLS
  • EDUCATOR_UNIVERSITY

Internet

  • INTERNET_DOMAINNAME
  • INTERNET_DOMAINSUFFIX
  • INTERNET_DOMAINWORD
  • INTERNET_EMAILADDRESS
  • INTERNET_IPV4ADDRESS
  • INTERNET_IPV4CIDR
  • INTERNET_IPV6ADDRESS
  • INTERNET_IPV6CIDR
  • INTERNET_MACADDRESS
  • INTERNET_PASSWORD
  • INTERNET_SLUG
  • INTERNET_URL
  • INTERNET_UUID

Job

  • JOB_FIELD
  • JOB_POSITION
  • JOB_SENIORITY
  • JOB_TITLE

Medical

  • MEDICAL_DISEASENAME
  • MEDICAL_HOSPITALNAME
  • MEDICAL_MEDICINENAME
  • MEDICAL_SYMPTOMS

Phone Number

  • PHONENUMBER_CELLPHONE
  • PHONENUMBER_PHONENUMBER

Text

  • TEXT_CHARACTER
  • TEXT_FIXEDSTRING
  • TEXT_PARAGRAPH
  • TEXT_SENTENCE
  • TEXT_WORD

Syntax

Anonymizer uses the following syntax:

    pii:fake(STRING input.string, String fake.function, BOOL invalidate.cache)

Query Parameters

NameDescriptionDefault ValuePossible Data TypesOptionalDynamic
input.stringThe input name to create a fake oneSTRINGNoYes
fake.functionThe key to be addedSTRINGNoYes
invalidate.cacheAn optional clean-up cache flag.

true - a different fake data will be generated at each call.

false - once generated, the fake data is cached to be used for the next calls
falseBOOLYesYes

Example

CREATE SOURCE patient_local WITH (type='database', collection='patient_local', replication.type="global", map.type='json') (full_name string, ssn string, email string, phone string);

CREATE TABLE GLOBAL patient_public(full_name string, ssn string, email string, phone string);

@info(name = 'anonymize')
INSERT INTO patient_public
SELECT pii:fake(full_name, "NAME_FULLNAME", true) as full_name,
pii:fake(ssn, "ID_SSN", false) as ssn,
pii:fake(email, "INTERNET_EMAILADDRESS", false) as email,
pii:fake(phone, "PHONENUMBER_PHONENUMBER", false) as phone
FROM patient_local;

The code block does the following:

  1. Insert following data into patient_local collection: {"full_name": "John Doe", "ssn": "123-123-123", "email": "John.Doe@macrometa.com", "phone": "123-123-12345"}

  2. Following document would be shown on the patient_public collection: {"full_name": "fake name", "ssn": "fake ssn", "email": "fake email", "phone": "fake phone number"}

This example shows how you might anonymize protected patient data. The patient needs to be hidden in the system so that he/she cannot be personally identified with it. Therefore, you need to obfuscate the value for the patient attributes.